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Chronicles of a prosumer – living by the sun

Smart Charging Webinar Series, 21/09/2021

Asso. Prof. Mattia Marinelli matm@elektro.dtu.dk

Center for Electric Power and Energy

DTU Risø Campus

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Academic positions

• Associate professor @ DTU since 02/2017 in the DER group

• Postdoc and researcher @ DTU (Denmark) between 09/2012 and 02/2017

• Postdoc @ University of Genova between 03/2011 and 08/2012

• Visiting PhD student at Eirgrid (Ireland) between 05/2010 and 09/2010 Degrees

• PhD in power systems (03/2011) from the University of Genova

• MSc in electrical engineering (10/2007) from the University of Genova (Italy) Research areas

1. Distributed energy resources (DER) modelling and experimental validation with focus on electric vehicles (EV) 2. Architecture of future low-inertia power systems with high share of DER

3. Control and operation of hybrid plants including wind, photovoltaic and storage

4. Multi-energy systems with focus on synergies between electrical, transportation and thermal domains

• Google scholar andScopus pages. And my DTU pagehere

• Didactic material from my courses is also available onYouTube and on my personalsite.

About me

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Outline

• Energy needs and CO

2

footprint

• On photovoltaic systems and net metering – self-sufficiency and own-consumption

• The flexibility of appliances…

• …and of EVs, including charging and degradation perspectives

• Lessons learned and next steps

(4)

• This presentation is not intended as full assessment of my carbon footprint…

• I am not here to lecture anyone on how to behave and what to do…

Disclaimer!

(5)

Energy needs overview of my house

• Heating:

- 8.8 MWh from district heating and 4.4 MWh from wood pellet (880 kg, @ 5 kWh/kg).

On an average year.

• Electricity:

- 2.3 MWh consumed by domestic appliances; 6.2 MWh produced by the 6 kW photovoltaic plant (after 2019).

• Gasoline car Honda Civic (1.3 16V) until end of 2020:

- 5.9 MWh equivalent to 10000 km (625 l, considering an average consumption of 16 km/l and 9.5 kWh/l).

• EV Nissan LEAF e-plus (62 kWh), from December 2020:

- 2.0 MWh equivalent to 10000 km (incl. charging efficiency). Note, the carbon footprint associated with the battery production should be added when doing a complete CO assessment.

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Energy needs old vs new – the role of PV and EV in decarbonizing

No PV, no EV (< 2019) Energy need

(MWh) Energy import

(MWh) Energy export

(MWh) CO2 emission factor

(g/kWh) CO2 footprint (ton)

Heating (DH & pellet)* 13.2 13.2 100 1.32

Electricity 2.3 2.3 135 0.31

CAR (gasoline) 5.9 5.9 250 1.48

SUM (2019) 21.4 21.4 0 3.11

PV but no EV (2020) Energy need

(MWh) Energy import

(MWh) Energy export

(MWh) CO2 emission factor

(g/kWh) CO2 footprint (ton)

Heating (DH & pellet)* 13.2 13.2 100 1.32

Electricity (50% self-suff) 2.3 1.1 -5.0 135 (grid); 20 (PV) (0.17-0.58) = -0.40

CAR (gasoline) 5.9 5.9 250 1.48

SUM (2020) 21.4 20.2 -5.0 2.39

PV & EV (2021) Energy need

(MWh) Energy import

(MWh) Energy export

(MWh) CO2 emission factor

(g/kWh) CO2 footprint (ton)

Heating (DH & pellet)* 13.2 13.2 100 1.32

Electricity (50% self-suff) 2.3 1.1 -4.0 135 (grid); 20 (PV) (0.17-0.46) = -0.29

EV (50% self-suff) 2.0 1.0 135 (grid); 20 (PV) 0.16

SUM (2021) 17.5 15.3 -4.0 1.19

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Energy needs old vs new – the role of PV and EV in decarbonizing

No PV, no EV (< 2019) Energy need

(MWh) Energy import

(MWh) Energy export

(MWh) CO2 emission factor

(g/kWh) CO2 footprint (ton)

Heating (DH & pellet)* 13.2 13.2 100 1.32

Electricity 2.3 2.3 135 0.31

CAR (gasoline) 5.9 5.9 250 1.48

SUM (2019) 21.4 21.4 0 3.11

PV but no EV (2020) Energy need

(MWh) Energy import

(MWh) Energy export

(MWh) CO2 emission factor

(g/kWh) CO2 footprint (ton)

Heating (DH & pellet)* 13.2 13.2 100 1.32

Electricity (50% self-suff) 2.3 1.1 -5.0 135 (grid); 20 (PV) (0.17-0.58) = -0.40

CAR (gasoline) 5.9 5.9 250 1.48

SUM (2020) 21.4 20.2 -5.0 2.39

PV & EV (2021) Energy need

(MWh) Energy import

(MWh) Energy export

(MWh) CO2 emission factor

(g/kWh) CO2 footprint (ton)

Heating (DH & pellet)* 13.2 13.2 100 1.32

Electricity (50% self-suff) 2.3 1.1 -4.0 135 (grid); 20 (PV) (0.17-0.46) = -0.29

EV (50% self-suff) 2.0 1.0 135 (grid); 20 (PV) 0.16

SUM (2021) 17.5 15.3 -4.0 1.19

Net energy need: 21.4 MWh → 11.3 MWh Carbon footprint: 3.11 ton → 1.19 ton

*the certified thermal need of the house was 26 MWh when purchased → reduced to 13.2 MWh with basic energy saving interventions and better temperature management in the rooms.

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Self-consumption and flexibility from appliances

• To get benefits from a residential photovoltaic system, one needs to self-consume as much as possible.

• This means that we need to search for “flexibility” among the appliances that we have in the house (from washing machines to electric stoves to electric vehicle) to match the photovoltaic production.

• What is flexibility with reference to appliances?

• The possibility to postpone appliances’ operation without compromising (too much) users’ expectation.

• AKA: start the dishwasher when the sun shines!

→ How to achieve the previously reported 50% in self-sufficiency?

(9)

The house (electrical perspective)

The supplier meter measures every second, but communication towards Datahub is done on a daily basis.

The Fronius smart meter has complete grid measurements, and communicate to the datalogger located inside the PV inverter (via RS-485).

Black line indicates power.

Red line communication.

The 6 kW PV inverter has 3p connection.

The 11 kW charger has 3p connection, though the LEAF will only charge up to 3.7 kW (6-16 A 1p)

(10)

Data logging availability and

self-sufficiency vs own-consumption

Energy measurements reported every 5 minutes -) PV production (average over 5 min)

-) Consumption (average over 5 min) -) Energy to grid (or export, positive)

-) Energy from the grid (or import, positive)

-) Consumed directly (PV production consumed in loco, meaning PV production - Export)

• Self-sufficiency (or self-consumption) is defined as the share of the consumption directly covered by the PV divided by the total consumption: [sum(Consumption) – sum(Import)] / [sum(Consumption)]

• Own-consumption is defined as the share of the consumption directly covered by the PV divided by the total PV production: [sum(Consumption) – sum(Import)] / [sum(PV production)]

(11)

Self-sufficiency (or self-consumption) in 2020 – 50%

(no EV yet)

• Self-sufficiency (or self-consumption) is defined as the share of the consumption directly covered by the PV divided by the total consumption: [sum(Consumption) – sum(Import)] / [sum(Consumption)]

• or [sum(PV production) – sum(Export)] / [sum(Consumption)]

(12)

PV production in 2020 – hourly pattern

• 6 kW PV system

• 20 – 300 W monocrystalline modules (positive tolerance) by Luxor

• https://www.luxor.solar/files/luxor/download/datash eets/LX_EL_M60_FB_310-

330W_1665x1002x35_1_19_158cs_EN_low.pdf

• 6 kW 3p inverter by Fronius

• https://www.fronius.com/en-gb/uk/solar- energy/installers-partners/technical-data/all-

products/inverters/fronius-symo/fronius-symo-6-0- 3-m

6.2 MWh of production in 2020 (1033 h/year).

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Behavioural driven flexibility consumption without PV

(Sep 2018 – Aug 2019) and with PV (Sep 2019 – Aug 2020)

• The evening peak got shifted towards midday

• I have calculated the hypothetical self-consumption I would have achieved if in that period (September 2018 - August 2019) I had had the PV.

• I obtained 35%, this means that because of the PV (or rather due to the intrinsic push to consume as much as possible what produced).

• → I managed to shift 15% of my consumption so to match what the Sun gives.

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Own-consumption in 2020 – 18% (no EV yet) target for 2021 is 33%

• Own-consumption is defined as the share of the consumption directly covered by the PV divided by the total PV production: [sum(Consumption) – sum(Import)] / [sum(PV production)]

• or [sum(PV production) – sum(Export)] / [sum(PV production)]

Average monthly

consumption ~200 kWh

(15)

About the profitability of a PV plant in DK – payback time – it’s all about own-consuming!

1 kW PV plant produces approx. 1 MWh/y in DK. Installation cost is 1500 €/kW. Estimated lifetime 30 years (assume no inverter replacement, no substantial loss of performance).

What is the payback time?

• If no own-consumption

→ Electricity price (market based): 42 €/MWh

→ payback time is 36 years.

• If 100% own-consumption

→ Electricity price (saved cost): 250 €/MWh

→ payback time is 6 years.

• If 33% own-consumption (target with EV)

→ Electricity price (weighted): 110 €/MWh

→ payback time is 13 years.

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Payback time – it’s all about own-consuming!

…and also higher energy prices

• If no own-consumption

→ Electricity price (market based): 84 €/MWh

→ payback time is 18 years.

• If 100% own-consumption

→ Electricity price (saved cost): 305 €/MWh

→ payback time is 5 years.

• If 33% own-consumption (target with EV)

→ Electricity price (weighted): 155 €/MWh

→ payback time is 9.5 years.

1 kW PV plant produces approx. 1 MWh/y in DK. Installation cost is 1500 €/kW. Estimated lifetime 30 years (assume no inverter replacement, no substantial loss of performance).

What is the payback time?

(17)

Does it matter how we measure power/energy?

One thing is if we add phases up (or not)

C. Ziras, L. Calearo, M. Marinelli, “The Effect of Net Metering Methods on Prosumer Energy Settlements,”

Sustainable Energy, Grids and Networks. Vol. 27, September 2021.

(18)

Does it matter how we measure power/energy?

Another is for how long we “net” (netting intervals)

Reporting interval is 1 hour in both cases, however:

• if netting interval is 1 second (instantaneous), we have 1.5 kWh of import and 0.5 kWh of export.

• If netting interval is 1 hour, we have 1 kWh of import and 0 kWh of export.

Summing up, over 2020 depending on the netting method, the self-sufficiency would have been:

➢ Summation per hour net: 55%

Summation per second net: 50%

➢ Per phase per second net: 40%

(19)

Consumption patterns – white appliances

Fridge & other gadgets (e.g., router, cameras…) Though small in power, this amounts to 40% of the base electricity consumption (no EV)

Washing machine

@ 40 deg

Dishwasher

(20)

Consumption patterns – electric stoves (values have an uncertainty of +/- 25 W)

145 mm 180 mm

Knob Power (W) Knob Power (W)

9 1400 9 1800

8 850 8 1200

7 550 7 800

6 400 6 500

5 & <5 300 ON/OFF 5 400

4 & <4 300 ON/OFF

210 mm 180 mm

Knob Power (W) Knob Power (W)

9 2300 9 1800

8 1450 8 1200

7 950 7 800

6 600 6 500

5 400 5 400

4 & <4 300 ON/OFF 4 & <4 300 ON/OFF To maximize self-consumption, it is better

to keep the power low and use it for longer time (but this decreases the overall heating efficiency 95% → 80%).

(21)

In the end, where is the flexibility among the domestic appliances?

Appliance Energy per cycle of usage (kWh)

Peak power (kW) & (A) Usage recurrence Recommended approach to use flexibility

Washing machine 1.0 – 1.5 kWh 1.8 kW

(8 A)

weekly Delayed start

Dishwasher 0.5 – 1.5 kWh 1.8 kW

(8 A)

daily Delayed start

Electric stoves* 0.1 – 1.0 kWh 0.4 – 2.3 kW (2 – 10 A)

daily Keep it low for long rather than high for short

Electric oven+ 0.5 – 1.5 kWh 2.3 kW

(10 A)

weekly None (useful to have smaller heating elements)

Vacuum cleaner 0.3 – 0.4 kWh 0.7 kW

(3 A)

weekly None (vacuum on daytime)

*) a meal with pasta requires around 0.4 – 0.6 kWh (most of the energy is needed to initiate boiling) +) a meal with pizza requires around 0.8 – 1.0 kWh (most of the energy is needed to heat up)

(22)

Now let’s move to the biggest source of flexibility…

…if parked at home!

(23)

How to handle the EV charging?

Let’s look at the energy needs first

• Assume 10000 km/year (2/3 of the Danish average driven distance) equal to 192 km/week or 27.4 km/day.

• Seen in terms of energy and considering a (conservative) energy consumption (including charging efficiency) of approx. 5 km/kWh this means: 2000 kWh/year equal to 38.4 kWh/week or 5.5 kWh/day.

• The key drivers/objectives while managing the charge of the EV are:

1. Avoid low charging power (for efficiency’s sake → user need): > 1.8 kW 2. Avoid high charging power (for grid’s sake → societal need): < 3.7 kW

3. Keep the EV charged to satisfy half-week demand (i.e., 19 kWh): > 30% SOC

4. Avoid keeping SOC too high (for degradation’s sake): < 90% (generally, the lower the better) 5. Take advantage of the sun when it shines… while keeping all above in mind!

→ Fulfilling all objectives is very challenging!

(24)

Assessment of the on-board charger efficiency

• DC measurements taken with LEAFspy, AC with a DEIF. SOC between 50% and 60%.

• The efficiency is calculated as ratio between DC and AC power values averaged over few minutes.

• Note, the EV was switched ON while taking the measurements, this caused an additional (constant) consumption of around 50 W, which was accounted for in the energy balance (normally the EV is OFF while charging).

76%

78%

80%

82%

84%

86%

88%

90%

92%

Efficiency

AC Power (W)

Onboard charger efficiency

L. Calearo, C. Ziras, K. Sevdari, M. Marinelli, Comparison of Smart Charging and Battery Energy Storage System for a PV Prosumer with an EV, ISGT 2021 conference

(25)

Charging with “granny cable” (left) and Wattpilot (right) – two charging sessions of almost 10 hours

Charged energy (AC side): 17.1 kWh

Estimated on the DC side: 14.2 kWh (83% eff.) Driving range @ 5.5 km/kWh: 78 km

Charged energy (AC side): 32.5 kWh

Estimated on the DC side: 28.6 kWh (88% eff.) Driving range @5.5 km/kWh: 157 km

Washing machine

@ 60 deg

(26)

Charging on a day with clouds passing over

(27)

Driving needs in Denmark

• Cars in Denmark drive on average 45 km/day (=16425 km/year).

And they drive (on average) 47 minutes per day, meaning that they are parked 96% of the time.

• In case of “granny cable” at 1.8 kW, the 10-hour charge can fill up 1/4 of the battery: 14.2 kWh (= 87 km @5.5 km/kWh).

This covers 80% of the daily driving needs.

• In case of “Wattpilot” charger at 3.7 kW, the 10-hour can fill up 1/2 of the battery: 28.6 kWh (= 157 km @5.5 km/kWh).

This covers 95% of the daily driving needs.

A. Thingvad, P.B. Andersen, T. Unterluggauer, C. Træholt, M. Marinelli,

“Electrification of Personal Vehicle Travels in Cities - Quantifying the Public Charging Demand,” e-transport, vol. 9, 2021.

(28)

Seen from the grid perspective – does it make sense to encourage high charging levels?

• 3.7 kW charger: max 40-42% EVs charging together in a population of 100 EVs

• 11 kW charger: max 20-22% EVs charging together in a population of 100 EVs

• Higher charging power means fewer EVs charging at same time, but higher overall peak consumption.

L. Calearo, A. Thingvad, K. Suzuki, M. Marinelli, “Grid Loading due to EV Charging Profiles Based on Pseudo-Real Driving Pattern and User Behaviour,” Transportation Electrification Transaction, vol. 5, 2019.

J. Bollerslev, P. B. Andersen, T. V. Jensen, M. Marinelli, A. Thingvad, L. Calearo, T. Weckesser, “Coincidence Factors for Domestic EV Charging

(29)

L. Calearo and M. Marinelli, “Profitability of Frequency Regulation by Electric Vehicles in Denmark and Japan Considering Battery Degradation Costs,” World Electr. Veh. J., vol. 11, no. 3, p. 48, 2020.

The fuss about degradation – calendar & cycling aging

(30)

How much does the battery degrade and how to quantify it? What is the nominal capacity?

• The battery of my LEAF e-plus has 288 (96x3) cells: each cell has 3.65 V nominal voltage and 58.8 Ah capacity.

Ideally, this means that the overall battery (energy) capacity should be: 288 * 3.65 V * 58.8 Ah = 61.8 kWh… right?

HOWEVER, according to the standard 62660-1 (Secondary lithium-ion cells for the propulsion of electric vehicles – Part 1: Performance testing), 2019:

1. there is no definition for nominal voltage: the closest thing is at page 16 and regard a so-called “average voltage calculation” (during discharge). Normally, cell voltage for NMC cells spans between 4.2 V and 2.8 V.

2. the definition of rated capacity is left to the manufacturer (see page 8). Moreover, this depends on what is the max/min voltage that the cell is allowed to operate (which can be changed over time): for example 4.2-3.0 V or 4.2-2.6 V

3. cells may not be identical → the overall battery capacity will not necessarily be the sum of all individual cells…

This means that the definition itself of battery capacity is arbitrary, and therefore the assessment of a battery health is a tricky job.

(31)

The problem in defining the capacity

Usable energy 95

Energy reserve 5

Usable energy 90

Over time, has the capacity reduced from 100 to 90 or from 95 to 90?

Meaning, is the degradation 5 or 10?

Which is the original capacity, 95 or 100?

How to quantify in a precise, standardized and replicable manner the state of health?

(32)

• Measurements are carried out on 24 kWh EVs offering 9.2 kW of frequency control 14 h/day (V2G bidirectional approach).

• Cars are driven little (10 km/day), but the cycling from frequency control amounts to an equivalent usage of 100 km/day.

• The solid line represent the expected degradation predicted by our degradation model.

A. Thingvad, L. Calearo, P. B. Andersen, M. Marinelli, “Empirical Capacity Measurements of Electric Vehicles Subject to Battery Degradation from V2G Service,” Vehicular Technology IEEE Transactions on, vol. 70, 2021.

Capacity measurements from the EVs providing

frequency regulation in Frederiksberg Forsyning

(33)

98.0%

98.2%

98.4%

98.6%

98.8%

99.0%

99.2%

99.4%

99.6%

99.8%

100.0%

0 30 60 90 120 150 180 210 240 270 300 330 360 390

SOH (%)

Days

State of health

Logbook of my LEAF (nearly 1 year of daily

measurements) based on LEAFspy measurements

Rolling average SOC = 62.6%.

Average ambient temp. 9.9 deg; Average battery temp. 13.7 deg

0 10 20 30 40

0 30 60 90 120 150 180 210 240 270 300 330 360 390

Number of cycles

Number of cycles (5.5 km/kWh)

-6 0 6 12 18 24 30 36

0 30 60 90 120 150 180 210 240 270 300 330 360 390

Temperature (C)

Days

Battery and ambient temperatures weekly averages

0%

20%

40%

60%

80%

100%

0 30 60 90 120 150 180 210 240 270 300 330 360 390

SOC (%)

Days

State of charge

Less than 1% in 1 year (?)

(34)

• Technologies for CO

2

reduction are there.

• Data is precious… and how we measure power/energy matters!

• The sun (PV plant) is harsh task master… but it’s all a question of training in the end.

• Avoid high power consumption and avoid usage of multiple appliances at the same time…

• … however, be wary of low-efficiency operating points.

• Behavioral flexibility is there but is limited (and often overestimated).

• Flexibility in EV charging is rather large and smart charging approaches should be encouraged.

• Next steps:

– LEAF e-plus degradation assessment.

– LEAF e-plus battery thermal and electrical characterization.

– A stationary battery at a certain point (for the fun of it and to make my wife happy)…

– …and/or a V2G (bidirectional) charger?

Conclusions and next steps!

(35)

• District heating: 100 g/kWh & Electricity from Danish grid 135 kg/kWh https://stateofgreen.com/en/partners/state-of- green/news/new-green-record-for-danish-electricity-lowest-co2-emissions-ever/

• PV: 20 g/kWh https://www.nature.com/articles/ncomms13728.pdf

• Wood pellet: 100 g/kWh *(0-400)* https://ens.dk/sites/ens.dk/files/Bioenergi/biomasseanalyse_final_ren_eng.pdf

• Battery footprint https://www.carbonbrief.org/factcheck-how-electric-vehicles-help-to-tackle-climate-change

References – CO2 emission factors

(36)

H2020 Insulae: demonstration activities on the island of Bornholm on technologies for energy

decarbonization;

• Danish funded

Topcharge: development and testing of a new innovative storage system for EV fast-charging

buffering

• EU

Interreg CAR: where solutions for e-mobility are tested across the Baltic region;

• Danish funded

ACDC: development and assessment of autonomous smart charging technology.

References – research project websites

(37)

• C. Ziras, L. Calearo, M. Marinelli, “The Effect of Net Metering Methods on Prosumer Energy Settlements,” Sustainable Energy, Grids and Networks.

Vol. 27, September 2021.

• A. Thingvad, P.B. Andersen, T. Unterluggauer, C. Træholt, M. Marinelli, “Electrification of Personal Vehicle Travels in Cities - Quantifying the Public Charging Demand,” e-transport, vol. 9, 2021.

• L. Calearo, A. Thingvad, K. Suzuki, M. Marinelli, “Grid Loading due to EV Charging Profiles Based on Pseudo-Real Driving Pattern and User Behaviour,” Transportation Electrification Transaction, vol. 5, 2019

• A. Thingvad, L. Calearo, P. B. Andersen, M. Marinelli, “Empirical Capacity Measurements of Electric Vehicles Subject to Battery Degradation from V2G Service,” Vehicular Technology IEEE Transactions on, vol. 70, 2021.

• L. Calearo and M. Marinelli, “Profitability of Frequency Regulation by Electric Vehicles in Denmark and Japan Considering Battery Degradation Costs,” World Electr. Veh. J., vol. 11, no. 3, p. 48, 2020.

• L. Calearo, M. Marinelli, C. Ziras, “A Review of Data Sources for Electric Vehicle Integration Studies,” Renewable & Sustainable Energy Reviews, vol. 151, 2021

• J. Bollerslev, P. B. Andersen, T. V. Jensen, M. Marinelli, A. Thingvad, L. Calearo, T. Weckesser, “Coincidence Factors for Domestic EV Charging from Driving and Plug-in Behavior,” Transportation Electrification, IEEE Transactions on. In press

• L. Calearo, C. Ziras, K. Sevdari, M. Marinelli, Comparison of Smart Charging and Battery Energy Storage System for a PV Prosumer with an EV, ISGT 2021 conference

• L. Calearo, M. Marinelli, C. Ziras, “A Review of Data Sources for Electric Vehicle Integration Studies,” Renewable & Sustainable Energy Reviews, vol. 151, 2021.

References

References

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